
Integreat -Norwegian Centre for Knowledge-driven Machine Learning · Oslo
About the positions Interested in pursuing a PhD in machine learning in an interdisciplinary and collaborative environment in Norway? Integreat - Norwegian C...
Interested in pursuing a PhD in machine learning in an interdisciplinary and collaborative environment in Norway?
Integreat - Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo and UiT The Arctic University of Norway invites applications for eight PhD fellowships connected to interdisciplinary projects in knowledge-driven machine learning. Four of the positions are co-funded with TRUST - The Norwegian Centre for Trustworthy AI. Integreat and TRUST provide a broader interdisciplinary research environment, offering all recruited candidates access to complementary expertise, scientific activities, and national research networks. The purpose of the fellowships is research training leading to the successful completion of a PhD degree. Successful applicants will be enrolled in the PhD programme at the University of Oslo or UiT The Arctic University of Norway.
Integreat brings together more than 100 researchers from mathematics, statistics, machine learning, logic, language technology, philosophy, and related fields. As a PhD fellow, you will become part of this interdisciplinary research community and work closely with researchers at different career stages across Integreat's partner institutions. You will also join an established cohort of early-career researchers and benefit from the centre's researcher development programme, including scientific seminars, interdisciplinary workshops, mentoring, career development activities, research mobility support, and social events.
The duration of each fellowship is specified in the individual project description. Most positions are three-year appointments. For selected projects, a four-year appointment may be offered, where the additional year is devoted to career-promoting tasks such as teaching, supervision, or other research-related duties outside the PhD project.
Starting date by agreement, depending on the project.
The place of work, either in Oslo or in Tromsø, is specified in each project description.
Integreat – Norwegian Centre for Knowledge-driven Machine Learning is a Centre of Excellence funded by the Research Council of Norway, with branches in Oslo at the University of Oslo and in Tromsø at UiT The Arctic University of Norway.
Machine learning is a core driver of artificial intelligence (AI) and an increasingly important force in a digital and data-driven world. Integreat develops theories, methods, models, and algorithms that combine data with general or domain-specific knowledge, helping lay the foundations for the next generation of machine learning. Integreat projects aim for more accurate, more sustainable, more explainable, and more trustworthy machine learning, with quantified uncertainty.
The centre brings together perspectives and methodologies from statistics, logic, language technology, theoretical computer science, ethics, and machine learning in new ways. Its research focuses on developing ground-breaking methods and theories for addressing fundamental challenges in science, technology, health, and society.
Integreat draws on the research strengths of researchers and students from the departments of Mathematics, Informatics, and Philosophy, the Oslo Centre for Biostatistics and Epidemiology at UiO, the Norwegian Computing Center (NR), and the machine learning group at UiT, with members from the departments of Physics and Technology, Mathematics and Statistics, and Computer Science.
TRUST is a Norwegian research centre dedicated to building the foundations of trustworthy AI. Its mission is to enable AI systems that are accurate, interpretable, inclusive, fair, safe, sustainable, and well-governed. By uniting expertise from (i) machine learning, statistics, mathematics and data science, (ii) law, and social sciences, and (iii) philosophy, the centre seeks to produce ground-breaking results tested on real-world problems, including healthcare, mobility, governance, security, and climate resilience.
In advancing trustworthy AI, TRUST will develop new AI technologies, support innovation, and investigate the societal consequences of AI, including the effects of AI on democracy, science, and the environment. With a consortium of over 70 partners from academia, industry, government and civil society in Norway and internationally, TRUST’s research is theoretical, methodological, legal, and empirical.
TRUST is funded by the Research Council of Norway and its public and private partners, and is led by the University of Oslo, SINTEF and the Norwegian Computing Center (NR).
Integreat and TRUST collaborate on selected research and training activities, creating opportunities for interaction across complementary research areas in machine learning and trustworthy AI. Through access to the scientific activities, expertise, and networks of both centres, recruited candidates will benefit from opportunities for scientific exchange, interdisciplinary collaboration, engagement with academic and non-academic partners, and participation in a wider national AI community.
See the information video for more information about Integreat.
Integreat seeks to recruit fulltime PhD fellows for eight cross-disciplinary projects spanning machine learning, statistics, logic, language technology, and ethics. The projects address fundamental challenges in modern machine learning and contribute to developing new theoretical and methodological foundations for the field.
As a PhD fellow, you will conduct independent research within one of the advertised projects under the supervision of leading researchers. You are expected to contribute actively to the research environment by participating in the centre's scientific activities, seminars, workshops, and collaborative initiatives.
Detailed information about each project, including the host department, PhD programme, starting date, and project-specific qualification requirements, is provided below and in the links.
Starting date: not earlier than 2 January 2027 and preferably as soon as possible thereafter
Starting date: not earlier than 2 January 2027 and preferably as soon as possible thereafter
Starting date: preferably in 2026, by agreement
Starting date: preferably in 2026, by agreement
Starting date: preferably in 2026, by agreement
Starting date: preferably in 2026, by agreement
Starting date: not earlier than 2 January 2027 and preferably as soon as possible thereafter
Starting date: not earlier than 2 January 2027 and preferably as soon as possible thereafter
We warmly invite prospective applicants to an online information meeting where representatives from Integreat and TRUST will introduce the research centres, present the PhD opportunities, and explain the application process. You will also have the opportunity to ask questions.
Attendance is optional but strongly encouraged.
(i) general qualification requirements applicable to all applicants, (ii) admission requirements for the relevant PhD programme, and (iii) project-specific requirements.
Applicants must satisfy all applicable requirements for every project they rank.
Employment and admission to the PhD programme are conditional upon successful completion of the Master's degree and submission of official documentation confirming that the degree has been awarded. Applicants who are in the final stages of completing their Master's degree may still apply.
i) General qualification requirements
For candidates with a foreign completed degree (M.Sc.-level), it must correspond to a minimum of four years in the Norwegian educational system.
ii) Project-specific requirements
Each project has a set of project-specific qualification requirements that are necessary for successful completion of the project. Before ranking a project, applicants must review the corresponding project description and ensure that they satisfy the project-specific requirements.
The purpose of the fellowships is research training leading to the successful completion of a PhD degree. Applicants must satisfy the admission requirements of the PhD programme associated with the project(s) they rank.
University of Oslo
Applicants must satisfy the admission requirements of the PhD programme at the Faculty of Mathematics and Natural Sciences, University of Oslo.
Education
Foreign education will be assessed to determine whether it is equivalent to the relevant Norwegian degree requirements.
Grade requirements
For applicants with foreign education, grades will be assessed in relation to the Norwegian grading scale as part of the admission process.
Further information about the UiO admission requirements
UiT The Arctic University of Norway
Applicants must satisfy the admission requirements of the PhD programme at the Faculty of Science and Technology, UiT The Arctic University of Norway.
Education
Grade requirements
Foreign education will be assessed in accordance with UiT's admission requirements.
Further information about the UiT admission requirements
We are looking for candidates who are curious, motivated to learn, and interested in tackling challenging scientific questions. You should be able to work independently while also contributing actively to collaborative research activities and the broader research community.
Integreat brings together researchers from different disciplines, institutions, and career stages. We value openness to new perspectives, effective communication, and a willingness to engage across disciplinary boundaries. We are looking for candidates who contribute positively to a supportive, inclusive, and respectful research environment.
UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no.
We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues—could you be the next one?
We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures.
If you have an immigrant background, a disability, or CV gaps, we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian).
The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports.
More information about gender equality initiatives at UiO can be found here.
Integreat is committed to equity, diversity, inclusion, and belonging, guided by our INTEGREAT principles (Integrity, Non-discrimination, Tact, Environment, Gratitude, Respect, Empathy, Accountability, Transparency). We embed these values in practice through inclusive hiring and structured evaluations, targeted mentoring and career development, and flexible work arrangements and accommodations to ensure everyone can thrive and contribute.
We have a clear institutional commitment to gender equality and diversity, with dedicated initiatives and networks for women in science.
We hope you will apply for the position with us.
Applications will be evaluated by expert committees appointed by the participating institutions. Applicants will be assessed against the general qualification requirements, the admission requirements of the relevant PhD programme, and the project-specific requirements for each project they rank and other relevant formal national and institutional regulations.
Applicants will be evaluated separately for each ranked project based on their academic qualifications and background, research experience, motivation, potential for research, and personal suitability for the project and research environment.
Where relevant and with the applicant's consent, the evaluation committee may also consider an applicant for other projects included in the call if the applicant's qualifications and research interests are deemed to be a strong match.
Shortlisted candidates will be invited to an online interview. References may be contacted as part of the final assessment.
If you have to relocate to Tromsø, the Faculty of Science and Technology may reimburse your moving costs. Further details regarding this matter will be made available if you receive an offer.
How to apply
Applicants with foreign education are advised to provide an official explanation of their institution's grading system.
Describe your motivation, research interests, and interest in the selected project(s).
Summary of your education, employment history, academic achievements, publications, and other relevant experience.
Include transcripts showing courses, credits, and grades, together with degree diplomas (DocumentType: BachelorDiploma and/or MasterDiploma) for Bachelor's and Master's degrees.
Upload your Master's thesis and any other academic work relevant to the application (DocumentType: AcademicWork). If your thesis has not yet been completed, upload a draft version.
Documentation of qualifications required by the ranked project(s), where applicable.
Upload documentation of English proficiency, where applicable.
Provide the names and contact details of 2–3 references, including their relationship to the applicant, email address, and telephone number. Reference letters are not required.
Required only for applicants who have not yet completed their Master's degree. Upload a statement from your supervisor or institution confirming the expected date of completion of the degree.
Successful candidates will be employed by the relevant host institution and are subject to the regulations governing employment and doctoral education in the Norwegian public sector. All qualified candidates will be assessed in accordance with applicable national export control, sanctions, and security regulations. Appointment is subject to the outcome of these mandatory checks.
Before commencement of employment, applicants must have completed their Master's degree and satisfy all relevant PhD admission requirements and be able to document that these requirements have been fulfilled, including any applicable English language requirements.
Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us.
Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian), Guidelines concerning appointment to post doctoral and research posts at UiO (Norwegian) and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo.
The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.
Further information for applicants and relevant regulations are available on UiT's website.
A shorter period of appointment may be decided when the PhD Fellow has already completed parts of their research training programme or when the appointment is based on a previous qualifying position as PhD Fellow, research assistant, or the like in such a way that the total time used for research training amounts to three years.
We process personal data given in an application or CV in accordance with the Personal Data Act (Offentleglova). According to the Personal Data Act information about the applicant may be included in the public applicant list, also in cases where the applicant has requested nondisclosure. You will receive advance notification in the event of such publication, if you have requested non-disclosure.
About the position We invite applications for position as PhD Research Fellow in computer science/AI for energy informatics available at the Department of Informatics (IFI), UiO Starting date: as soon as possible, no later than Sept. 2026. The fellowship period is three years. Depending on the candidate and the teaching needs of the department, the fel-lowship period can be extended either for compulsory work consisting of e.g., teaching and supervision duties and research assistance up top four years. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Place of work is the Department of Informatics at Forskningsparken, Oslo. Job description Description about scope of the PhD research: Do you have a background in energy informatics, computer science, or energy systems, and are you are interested in edge intelligence, multi-agent AI, and interdisciplinary collaborative research, and looking for a PhD position, this opportunity can be for you. The Energy Informatics EI@ND Networks and Distributed Systems group at the Department of Informatics (IFI), University of Oslo (UiO) is seeking a highly motivated PhD candidate for a fully funded full time PhD position for the Norwegian National AI Center on AI for Decisions (aiD). The fellowship is for research training for a period of 3 years leading to the successful completion of a PhD degree. As a PhD candidate with us, you will gain valuable experience opening up exciting career opportunities in academia and industry. About the Project: The position will be part of AID, the Norwegian Centre on AI for Decisions, an interdisciplinary national AI centre in Norway led by NTNU and SINTEF. AID brings together academic institutions, research organizations, and more than 50 professional organizations. Its primary objective is to advance AI for decision-making through fundamental research and real-world use cases, ensuring that AI-enhanced human decisions and autonomous systems are effective, safe, and trustworthy in sectors critical to society. The global energy system is undergoing a profound transformation driven by the rapid uptake of distributed renewable energy resources and the envisioned empowerment of prosumers. Thus, the traditional centralized grid is evolving into a highly distributed, data/ computation-intensive, AI-driven ecosystem in which smart meters, microgrids, aggregators, and edge devices actively participate in energy production, storage, consumption, and market interactions. This transition is fundamentally reshaping the structure of energy networks, shifting from centralized control to distributed, prosumer-driven ecosystems where interconnected multi-agents interact strategically in dynamic and uncertain environments. While Artificial Intelligence (AI) optimizes predictions or policies, energy systems are inherently multi-agent, strategic, and resource-constrained. Each agent has its own objective (e.g, cost, profit, comfort, sustainability, etc.) and interacts with other agents for shared resources (e.g., grid capacity, energy prices). In this new paradigm therefore, multiple autonomous agents including households, aggregators, and grid operators-must make real-time, interdependent decisions under shared constraints and competing objectives. Multi-agent learning and optimization show promise in this regard. Yet, the deployment of AI for decision making in critical infrastructure like the energy sector introduces challenges related to safety, fairness, accountability, transparency, and explainability (FATE), as well as compliance with emerging regulatory frameworks such as the EU AI Act and Data Act. More About the Position: In this project, you will develop game-theoretic AI frameworks by integrating Data-driven intelligence with principled decision structure for multi-agent decision making in energy systems. In addition, you will derive formal FATE metrics for the energy system and develop Explainable AI solutions to ensure transparency while also addressing privacy preservation and computation-efficiency requirements at the energy edge. Further, you will incorporate compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market optimization (demand response, transactive energy peer-to-peer trading, and renewable integration) and (energy edge+) distribution grid resilience. Duties of the position: • Carry out research of high quality within the scope and framework described above • Actively Participate in activities of the Energy Informatics/ND research group • Complete academic training consisting of coursework corresponding to a minimum 30 ECTS • Produce publications of exceptional quality in relevant conferences, journals and actively contribute in popular science dissemination • Participate in international activities such as conferences and/or research stays in foreign educational institutions What skills are important in this role? The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials. Required qualifications: • Master’s degree (120 credits equivalent of the Norwegian Master’s degree program) in Electrical Engineering, Communication Engineering, Computer Science or other relevant discipline, with a Master Thesis in the Master’s degree program. • Foreign completed degree (M.Sc.level) corresponding to a minimum of four years in the Norwegian educational system • Must have documented solid mathematical foundations on optimization (e.g., optimization modelling and numerical optimization), game theory, AI/ML (A focus on explainable AI e.g., will be valuable) • Must have documented Background/Knowledge on Energy/Systems/Energy Informatics and edge intelligence etc. • Must have documented significant Knowledge/Research Background, or Must be able to demonstrate skills on Data Analytics and Machine Learning, in particular on distributed ML. • Must have very good programming competence in Python, Java, C/C++ or equivalent • Fluent oral and written communication skills in English Desired qualifications: • Publications in reputed journals and conferences in the field • Excellent presentation skills • Experience working in an cross-disciplinary/International Team Language requirement: • Good oral and written communication skills in English • English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows: • The average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system • The average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system • The Master’s thesis must have the grade B or better in the Norwegian educational system For more information see: The purpose of the fellowship is research training leading to the successful completion of a PhD degree. All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based on these checks. Primary checkpoints are the Export Control regulation, the Sanctions regulation, and the national security regulation. What are we looking for in you? Personal skills: • Ability to work both independently and as part of a team • Ability to work precise in a structured manner and swiftly adapts to new tasks • Good communication and collaboration skills • Positive attitude and the ability to handle hectic periods The candidate should demonstrate: • strong motivation, curiosity, proactiveness and a learning-oriented mindset • capability to work independently, take initiative, and maintain good structure and discipline in their work • communicate effectively and collaborate well with supervisors and peers • resilience and work constructively when facing challenges or setbacks • integrity and a strong sense of responsibility in their research conduct • high interest and motivation for collaboration with industrial and interdisciplinary teams • ability to write in a structured, clear and concise manner The evaluation considers many aspects of excellence, as well as the personal drive and organizational skills. The candidate should also possess good interpersonal and communication skills and show high level of motivation to work as part of an international team. Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including personal qualifications. We can offer you • A pleasant and stimulating work environment • Good welfare schemes • Opportunity of up to 1.5 hours a week of exercise during working hours • A workplace with good development and career opportunities • Career development programmes • Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes • Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities • Salary in position as PhD Research Fellow, position code 1017 in salary range NOK from 550 800 - 595 000, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund We need different perspectives in our work UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no. We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues, could you be the next one? We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures. If you have an immigrant background, a disability, or CV gaps (Norwegian), we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian). The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality initiatives at UiO can be found here. We hope you will apply for the position with us. How to apply The application must include: • Cover letter - statement of motivation and research interests • CV (summarizing education, positions and academic work - scientific publications) • Copies of the original Bachelor and Master’s degree diploma and transcripts of records • Three letters of recommendation • Names and contact details of three references (name, relation to candidate, e-mail and telephone number) • Documentation of English proficiency if applicable • List of publications and academic work that the applicant wishes to be considered by the evaluation committee Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for this job". Foreign applicants should attach an official explanation of their University's grading system. When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language. General information The best qualified candidates will invited for interviews. Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us. Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian), Guidelines concerning appointment to post doctoral and research posts at UiO (Norwegian) and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo. The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.
About the position We invite applications for position as Postdoctoral Research Fellow in statistics and data science available at Department of Mathematics. Preferred starting date as soon as possible. The fellowship period is three years. No one can be appointed for more than one Postdoctoral Research Fellowship at the University of Oslo. The place of work is Department of mathematics at Blindern Campus, Oslo. The position is associated with the newly established Norwegian Maritime AI Centre (MAI), a national initiative for research, innovation, and education in artificial intelligence for the maritime sector. Here you will work together with students, PhD candidates and researchers, as well as world leading industry partners. The candidate will be affiliated with the Statistics and Data Science Section. The section is active in many areas of applied and theoretical statistics and data science, and is heavily involved in research at the crossing of statistics and machine learning. The focus of this postdoctoral fellowship is to conduct cutting-edge research on AI-based forecasting and analytics for shipbroking and maritime decision support. The aim is to develop and analyze advanced models that integrate heterogeneous maritime data sources - such as AIS, metocean, emissions, port, cargo, and business data - to improve predictions of costs, freight rates, delays, emissions, and port logistics. While strongly rooted in real-world industrial use cases, the position has a clear academic orientation to develop advanced models for data rich environments. The successful candidate is expected to contribute to the methodological foundations of maritime AI, publish in leading international journals and conferences, and collaborate closely with MAI’s academic and industrial partners to advance safe, transparent, and trustworthy AI in the maritime sector. The main purpose of a postdoctoral fellowship is to provide the candidates with enhanced skills to pursue a scientific top position within or beyond academia. In addition to the activities in MAI, the project will benefit from a large machine learning research environment in the Norwegian Center for Knowledge‑driven Machine Learning (Integreat) hosted by the Section for Statistics and Data Science at the Department of Mathematics. Qualifications The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials. Required qualifications: • Applicants must hold a degree equivalent to a Norwegian doctoral degree in statistics, applied mathematics, machine learning, computer science, operations research or a similar field. Doctoral dissertation must be submitted for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defense are eligible for appointment. • The applicant is required to document that the degree corresponds to the profile of the post. • Documented knowledge of statistical theory and methods and core machine learning methods. • Documented Python programming skills. • Excellent skills in written and oral English. • The candidate's research proposal must be closely connected to the call and the research of MAI. • Personal suitability and motivation for the position. Desired qualifications (advantageous, but not necessary): • PhD thesis or later research relevant for the position. • Experience with interdisciplinary research, bridging the gap between academic methodological development and industrial applications. • Relevant experience with data from the maritime sector. The University of Oslo is subject to the Norwegian Security Act, which sets requirements for the handling of protected information, in addition to other relevant legislation on sensitive information. It is therefore a requirement for employment that the candidate is personally suitable from a security perspective. Please note that prospective candidates may be asked questions to determine this. Background checks may be performed. It is a requirement for this position that the candidate is eligible to receive a national security clearance at level K. What are we looking for in you? Personal skills: • Ability to work both independently and as part of a team • Ability to work precisely and in a structured manner, and to adapt quickly to new tasks • Good communication and collaboration skills • Positive attitude and the ability to handle hectic periods • Solution oriented Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including personal skills. We can offer you • A friendly and stimulating work environment • Good welfare schemes • Opportunity of up to 1.5 hours a week of exercise during working hours. • A workplace with good development and career opportunities • Career development programmes • Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes • Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities • Salary in position as Postdoctoral Fellow, position code 1352 in salary range NOK 595 000 - 690 000, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund We need different perspectives in our work UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no. We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues, could you be the next one? We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures. If you have an immigrant background, a disability, or CV gaps (Norwegian), we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian). The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality initiatives at UiO can be found here. We hope you will apply for the position with us. How to apply The application must include: • Cover letter - statement of motivation and research interests • Curriculum Vitae (CV) summarizing education, positions, pedagogical experience, administrative experience, a complete list of publications and other qualifying activity • One-page research proposal relevant to the position stating research questions and methodological approaches • Copies of educational certificates, academic transcript of records • Documentation of English proficiency if applicable • A complete list of publications and up to 3 academic works (pdf files attached to the application or web links to open-access of full version of published papers) that the applicant wishes to be considered by the evaluation committee • Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number) Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for this job". When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language. General information The best qualified candidates will invited for interviews. Please see the guidelines and regulations for appointments to Postdoctoral fellowships at the University of Oslo. If an applicant has applied for and been granted funding for a fulltime research stay abroad while being employed as a Postdoctoral Research Fellow, the employment will be prolonged with the equivalent time as the research stay, but for no longer than of twelve months ( thus extending the employment to a maximum of four years) No one can be appointed twice as a Postdoctoral fellow financed with funds from The Research Council of Norway (NFR). Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us. The University of Oslo has an agreement for all employees, aiming to secure rights to research results a.o.
About the position We invite applications for position as PhD Research Fellow in Statistics and Data Science available at Department of Mathematics. Preferred starting date as soon as possible. The fellowship period is three years. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. The place of work is Department of mathematics at Blindern Campus, Oslo. The position is associate with the newly established Norwegian Maritime AI Centre, a national initiative for research, innovation, and education in artificial intelligence for the maritime sector. Here you will work together with other PhD candidates and researchers, as well as world leading industry partners. The candidate will be affiliated with the Statistics and Data Science Section. The section is active in many areas of applied and theoretical statistics and data science, and is heavily involved in research at the crossing of statistics and machine learning. Modern vessels produce vast amounts of multivariate data streams. The project addresses the development of trustworthy statistical and machine learning methods for anomaly detection in such streaming data (time series), potentially extended to spatio‑temporal settings. The emphasis is on online, real‑time detection, which imposes strict constraints on the computational efficiency and latency of the detector. The candidate will develop generic, broadly applicable methods that can be adapted for monitoring the state, performance and health of maritime equipment and systems, as well as for maritime traffic surveillance. The project will benefit from the anomaly detection research environment in the Norwegian Center for Knowledge‑driven Machine Learning (Integreat) and the ongoing project Statistical Methods for Online Detection of Anomalies (SODA), providing supervision and collaborators with expertise that spans from maritime applications to the derivation of theoretical guarantees. What skills are important in this role? The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials. Required qualifications: • Master’s degree or equivalent in statistics, mathematics, machine learning, computer science or a similar field • Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system • Documented knowledge of statistical theory and methods and core machine learning methods • Documented Python programming skills Desired qualifications: • Experience with change point detection and anomaly detection • Relevant experience with data from the maritime sector Language requirement: • Good oral and written communication skills in English • English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows: • The average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system • The average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system • The Master’s thesis must have the grade B or better in the Norwegian educational system For more information see: The purpose of the fellowship is research training leading to the successful completion of a PhD degree. The University of Oslo is subject to the Norwegian Security Act, which sets requirements for the handling of protected information, in addition to other relevant legislation on sensitive information. It is therefore a requirement for employment that the candidate is personally suitable from a security perspective. Please note that prospective candidates may be asked questions to determine this. Background checks may be performed. It is a requirement for this position that the candidate is eligible to receive a national security clearance at level K. What are we looking for in you? Personal skills: • Ability to work both independently and as part of a team • Ability to work precise in a structured manner and swiftly adapts to new tasks • Good communication and collaboration skills • Positive attitude and the ability to handle hectic periods • Solution oriented Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including personal qualifications. We can offer you • A pleasant and stimulating work environment • Good welfare schemes • Opportunity of up to 1.5 hours a week of exercise during working hours • A workplace with good development and career opportunities • Career development programmes • Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes • Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities • Salary in position as PhD Research Fellow, position code 1017 in salary range NOK from 550 800 - 595 000, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund We need different perspectives in our work UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no. We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues, could you be the next one? We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures. If you have an immigrant background, a disability, or CV gaps (Norwegian), we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian). The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality initiatives at UiO can be found here. We hope you will apply for the position with us. How to apply The application must include: • Cover letter - statement of motivation and research interests • CV (summarizing education, positions and academic work - scientific publications, if applicable) • Copies of the original Bachelor and Master’s degree diploma and transcripts of records • Documentation of English proficiency if applicable • List of publications (if applicable) and academic work that the applicant wishes to be considered by the evaluation committee • Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number) Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for this job". Foreign applicants should attach an official explanation of their University's grading system. When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language. General information The best qualified candidates will invited for interviews. Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us. Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian), Guidelines concerning appointment to post doctoral and research posts at UiO (Norwegian) and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo. The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.